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The paper "The Pursuit of Pseudocode Programming: Can LLMs Bridge the Gap?" explores the potential of Large Language Models (LLMs) to make pseudocode executable, addressing long-standing challenges in pseudocode programming. Pseudocode, known for its human-readable style, has been valuable for planning, communication, and education but has faced issues like lack of standardization, ambiguity, and limited expressiveness. LLMs offer new possibilities by handling ambiguity, generating code from pseudocode, and enhancing its expressiveness. Recent developments like SudoLang and pseudocode injection techniques demonstrate the potential of LLMs in this area. However, challenges remain in ensuring accuracy, reliability, and ethical considerations of LLM-generated code.
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Ken Kahn created a Chrome extension with the help of ChatGPT 4o that provides the contextual meaning of words selected on web pages. The extension prompts an LLM to provide a brief definition of the selected word within its context. The project involved generating files for a Chrome extension, replacing alerts with custom popups, and enhancing the sentence-finding feature.
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